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KDD
2012
ACM
201views Data Mining» more  KDD 2012»
11 years 10 months ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
SSDBM
2006
IEEE
121views Database» more  SSDBM 2006»
14 years 1 months ago
Time Series Analysis Using the Concept of Adaptable Threshold Similarity
The issue of data mining in time series databases is of utmost importance for many practical applications and has attracted a lot of research in the past years. In this paper, we ...
Johannes Aßfalg, Hans-Peter Kriegel, Peer Kr...
AUSAI
2008
Springer
13 years 9 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan
GFKL
2007
Springer
164views Data Mining» more  GFKL 2007»
13 years 11 months ago
Classification with Invariant Distance Substitution Kernels
Kernel methods offer a flexible toolbox for pattern analysis and machine learning. A general class of kernel functions which incorporates known pattern invariances are invariant d...
Bernard Haasdonk, Hans Burkhardt
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 5 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone